Overview
- Is a collection of applications of data analytics and machine learning in public procurement and supply chain management
- Emphasizes the most cutting-edge methods proposed in recent years
- Presents the context of data mining techniques, artificial intelligence, and the role of new technologies
Part of the book series: Asset Analytics (ASAN)
Included in the following conference series:
Conference proceedings info: ICDAPS 2022.
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Table of contents (35 papers)
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Applications of Emerging Technologies and AI/ML Algorithms
Keywords
About this book
This book provides practical insights into applications of the state-of-the-art of Machine Learning and Artificial Intelligence (AI) for solving intriguing and complex problems in procurement and supply chain management. The application domain includes perishable food supply chain, steel price prediction, electric vehicle charging infrastructure design, contract price negotiation, reverse logistics network design, and demand forecasting. Further, the book highlights the advanced topics in the procurement field, like AI in green procurement and e-procurement in the pharma sector. Furthermore, the book covers applications of well-established methodologies such as heuristics, optimization, game theory, and MCDM based on the nature of the problem. The inclusion of the vaccine supply chain digital twin and blockchain-based procurement signals the significance of the book. This book is a comprehensive guide for industry professionals to understand the power of data analytics, enabling them to improve efficiency and effectiveness in the procurement and supply chain sectors.
Editors and Affiliations
About the editors
Prof. Madhu Ranjan Kumar IRSS (Retd) heads the Procurement Research Centre (PRC) at Arun Jaitley National Institute of Financial Management (AJNIFM), Faridabad, India. The recent research areas of Prof. Kumar are use of data analytics in Reverse Auction and in pricing of bids. He is a Fellow of Indian Institute of Materials Management and a Fellow of Institution of Engineers. He is a Mechanical Engineer from IIT BHU and doctorate from Southern Cross University, Australia.
Dr. Rofin T. M. is currently working as an Assistant Professor in the area of Operations and Supply Chain Management at National Institute of Industrial Engineering (NITIE), Mumbai. He obtained his PhD from the Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur. His research work is concerned with game-theoretic modelling of emerging multi-channel supply chain configurations, EPC contracts, Electric Vehicle Charging Supply Chain and Supply Chain Risk and Resilience. He has more than 6 years of teaching experience at the post graduate level. He is a lifetime member of Operational Research Society of India.
Rony Mitra is a research scholar at the Indian Institute of Technology (IIT) Kharagpur with the Department of Mathematics. He completed his B.Sc in Mathematics and MTech in Computer Science and Data Processing. His areas of research interest are financial mathematics, financial modeling, stochastic processes, asset pricing, risk management, time series, portfolio management, supply chain management, data structures, etc. He developed innovative solutions for various industrial challenges, including predictive maintenance for baggage handling systems, sales forecasting for a multinational retail company, turn around time reduction for an Indian Port.
Bibliographic Information
Book Title: Applications of Emerging Technologies and AI/ML Algorithms
Book Subtitle: International Conference on Data Analytics in Public Procurement and Supply Chain (ICDAPS2022)
Editors: Manoj Kumar Tiwari, Madhu Ranjan Kumar, Rofin T. M., Rony Mitra
Series Title: Asset Analytics
DOI: https://doi.org/10.1007/978-981-99-1019-9
Publisher: Springer Singapore
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
Hardcover ISBN: 978-981-99-1018-2Published: 02 July 2023
Softcover ISBN: 978-981-99-1021-2Due: 02 August 2023
eBook ISBN: 978-981-99-1019-9Published: 01 July 2023
Series ISSN: 2522-5162
Series E-ISSN: 2522-5170
Edition Number: 1
Number of Pages: XII, 408
Number of Illustrations: 18 b/w illustrations, 84 illustrations in colour
Topics: Supply Chain Management, Computer Science, general, Procurement, Machine Learning, Statistics, general